{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "7ba67687",
   "metadata": {},
   "source": [
    "1、读取文本文件test1.txt（英文）进行词语统计。讲统计结果降序排序后（序号、词语、频率）存放到test1.csv 。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "059d1f6b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['a', 'a', 'a', 'b', 'b', 'c']"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re\n",
    "from collections import Counter\n",
    "with open(r\"1\\test2.txt\",\"r\") as f:\n",
    "    str1=f.read()\n",
    "arry1=re.split(\"[,.\\n]\",str1)\n",
    "arry1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "36297716",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>单词</th>\n",
       "      <th>频率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>a</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>b</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>c</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  单词  频率\n",
       "0  a   3\n",
       "1  b   2\n",
       "2  c   1"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "words=Counter(arry1)\n",
    "list1=sorted(words.items(),key=lambda x:x[1],reverse=True)#items（）\n",
    "#忘记words.items()和key=\n",
    "import pandas as pd\n",
    "df=pd.DataFrame(list1,columns=[\"单词\",\"频率\"])\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "91ca21e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "df.to_csv(\"test2.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "60ebc600",
   "metadata": {},
   "source": [
    "2、设计一个类 Person，需满足以下要求：\n",
    "属性设计：根据人员的实际特性，设计并实现必要的属性（如姓名、性别。。。等），并为每个属性设置合理的访问控制（私有、只读、可修改等）。\n",
    "构造方法：实现一个构造方法，用于初始化Person对象的基本属性。\n",
    "核心方法：实现以下方法，模拟人员的基本操作，比如：\n",
    "getup()：起床\n",
    "eat(foodname)：吃饭。\n",
    "speak(content)：说话。\n",
    "。。。。\n",
    "约束条件：\n",
    "请自行设计一些约束条件，比如：\n",
    "1）睡觉时不能吃饭。\n",
    "。。。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "37cc6d1b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "黑山老妖起床了\n",
      "他在讲'我饿了'\n",
      "黑山老妖正在吃肉\n"
     ]
    }
   ],
   "source": [
    "class Person:\n",
    "    #def __init__(name,gender,age):\n",
    "    def __init__(self,name,gender,age):\n",
    "        self._name=name\n",
    "        self.gender=gender\n",
    "        self.age=age\n",
    "        self._is_sleeping=False\n",
    "    @property\n",
    "    def name(self):\n",
    "        return self._name\n",
    "    def getup(self):\n",
    "        if self._is_sleeping==False:\n",
    "            print(f\"{self.name}起床了\")\n",
    "        else:\n",
    "            print(f\"{self.name}在睡觉\")\n",
    "    def eat(self,foodname):\n",
    "        if not self._is_sleeping:\n",
    "            print(f\"{self.name}正在吃{foodname}\")\n",
    "        else:\n",
    "            print(f\"{self.name}在睡觉，不能吃东西\")\n",
    "    def speak(self,content):\n",
    "        if self._is_sleeping:\n",
    "            print(f\"{self.name}在睡觉，没说话\")\n",
    "        else:\n",
    "            print(f\"他在讲'{content}'\")\n",
    "if __name__==\"__main__\":\n",
    "    a=Person(name=\"黑山老妖\",gender=\"男\",age=26)\n",
    "    a.getup()\n",
    "    a.name\n",
    "    a.speak(\"我饿了\")\n",
    "    a.eat(\"肉\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f667a26c",
   "metadata": {},
   "source": [
    "3、请设计一个利用Condition/ Queue对象实现多线程同步案例。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "66e205f8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "生产者正在发送0\n",
      "生产者正在发送1\n",
      "生产者正在发送2\n",
      "消费者正在接收0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "生产者正在发送3\n",
      "生产者正在发送4\n",
      "消费者正在接收1\n",
      "生产者正在发送5\n",
      "生产者正在发送6\n",
      "消费者正在接收2\n",
      "生产者正在发送7\n",
      "生产者正在发送8\n",
      "消费者正在接收3\n",
      "生产者正在发送9\n",
      "消费者正在接收4\n",
      "消费者正在接收5\n",
      "消费者正在接收6\n",
      "消费者正在接收7\n",
      "消费者正在接收8\n",
      "消费者正在接收9\n"
     ]
    }
   ],
   "source": [
    "import threading\n",
    "import time\n",
    "import queue\n",
    "\n",
    "class producer(threading.Thread):\n",
    "    def __init__(self,name1):\n",
    "        #self.name=name\n",
    "        threading.Thread.__init__(self,name=name1)\n",
    "    def run(self):\n",
    "        for i in range(10):\n",
    "            myqueue.put(i)\n",
    "            print(f\"{self.name}正在发送{i}\")\n",
    "            time.sleep(0.8)\n",
    "class consumer(threading.Thread):\n",
    "    def __init__(self,name1):\n",
    "        threading.Thread.__init__(self,name=name1)\n",
    "        #self.name=name\n",
    "    def run(self):\n",
    "        for i in range(10):\n",
    "            myqueue.get()\n",
    "            print(f\"{self.name}正在接收{i}\")\n",
    "            time.sleep(1.5)\n",
    "myqueue=queue.Queue()\n",
    "#producer(\"生产者\").run()\n",
    "producer(\"生产者\").start()\n",
    "time.sleep(2)\n",
    "#consumer(\"消费者\").run()\n",
    "consumer(\"消费者\").start()\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "25b89855",
   "metadata": {},
   "source": [
    "4、数据文件 “test.csv”中读取xx数据，并用柱形图/饼图/散点/雷达图展示，要求数据上面有标签，使用中文字体，图表保存到data目录。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "43bef425",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.rcParams[\"font.sans-serif\"]=\"SimHei\"\n",
    "plt.rcParams[\"axes.unicode_minus\"]=False\n",
    "\n",
    "df1=pd.read_excel(r\"4\\plot.xlsx\",sheet_name=\"bar1\")\n",
    "x,y=df1[\"年份\"],df1[\"销售额\"]\n",
    "\n",
    "plt.figure(figsize=(5,3))\n",
    "#plt.bar(x,y,label=\"销售额\",c=\"b\",width=0.6)\n",
    "plt.bar(x,y,label=\"1\",color=\"r\",width=0.6)\n",
    "plt.legend()\n",
    "plt.xlabel(\"年份\")\n",
    "plt.ylabel(\"销售额\")\n",
    "plt.savefig(\"bar.png\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ba589dd8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd \n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "df2=pd.read_excel(r\"4\\plot.xlsx\",sheet_name=\"scatter\")\n",
    "x,y1,y2=df2[\"月份\"],df2[\"广告费用\"],df2[\"销售收入\"]\n",
    "plt.figure()\n",
    "plt.scatter(x,y1)\n",
    "plt.xlabel(\"月份\")\n",
    "plt.ylabel(\"广告费用\")\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cd369a64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '雷达图')"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "plt.rcParams[\"font.sans-serif\"]=\"SimHei\"\n",
    "plt.rcParams[\"axes.unicode_minus\"]=False\n",
    "\n",
    "df1=pd.read_excel(r\"4\\plot.xlsx\",sheet_name=\"bar1\")\n",
    "x,y=df1[\"年份\"],df1[\"销售额\"]\n",
    "# x=np.concatenate(x,[x[0]])\n",
    "# y=np.concatenate(y,[y[0]])\n",
    "#list=[x,x[0]] 只是创建了一个包含两个元素的列表，并没有连接数组\n",
    "x1=np.linspace(0,2*np.pi,len(y),endpoint=False)\n",
    "x1=np.concatenate((x1,[x1[0]])))\n",
    "y1=np.concatenate((y,[y[0]]))\n",
    "\n",
    "plt.figure()\n",
    "ax1=plt.subplot(111,polar=True)\n",
    "ax1.plot(x1,y1)\n",
    "ax1.fill(x1,y1,alpha=0.3)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5b6b06db",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "d77b8c3b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>年份</th>\n",
       "      <th>销售额</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2014</td>\n",
       "      <td>1962035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2015</td>\n",
       "      <td>2838693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2016</td>\n",
       "      <td>2317447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2017</td>\n",
       "      <td>2335002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2018</td>\n",
       "      <td>2438570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2019</td>\n",
       "      <td>1675591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2020</td>\n",
       "      <td>3568120</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     年份      销售额\n",
       "0  2014  1962035\n",
       "1  2015  2838693\n",
       "2  2016  2317447\n",
       "3  2017  2335002\n",
       "4  2018  2438570\n",
       "5  2019  1675591\n",
       "6  2020  3568120"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.rcParams[\"font.sans-serif\"]=\"SimHei\"\n",
    "plt.rcParams[\"axes.unicode_minus\"]=False\n",
    "\n",
    "df=pd.read_excel(r\"4\\plot.xlsx\",sheet_name=\"bar1\")\n",
    "\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "09f44e92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x,y=df[\"年份\"],df[\"销售额\"]\n",
    "plt.pie(x=y,labels=x,autopct=\"%.1f%%\")\n",
    "plt.title(\"2014-2020年销售额占比\")\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "669a9e9c",
   "metadata": {},
   "source": [
    "5、请设计一个Python多态（polymorphism）案例并通过主程序调用展示多态特性。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "6e34412e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "汪汪\n",
      "猫喵喵\n"
     ]
    }
   ],
   "source": [
    "\n",
    "class animal(object):\n",
    "    def __init__(self,name):\n",
    "        self.name=name\n",
    "    def speak(self):\n",
    "        pass\n",
    "class dog(animal):\n",
    "    def __init__(self,name):\n",
    "        super().__init__(name)\n",
    "    def speak(self):\n",
    "        print(\"汪汪\")\n",
    "class cat(animal):\n",
    "    def __init__(self,name):\n",
    "        super().__init__(name)\n",
    "    def speak(self):\n",
    "        print(self.name+\"喵喵\")\n",
    "\n",
    "if __name__==\"__main__\":\n",
    "    dog1=dog(\"狗\")\n",
    "    dog1.speak()\n",
    "    cat1=cat(\"猫\")\n",
    "    cat1.speak()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd06a820",
   "metadata": {},
   "source": [
    "6、请设计一个Python抽象基类（Abstract Base Classes, ABC）案例，并在主程序中调用展示抽象特性。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "c02e2fff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "314.0\n"
     ]
    }
   ],
   "source": [
    "from abc import ABC,abstractmethod\n",
    "class shape(ABC):\n",
    "    def __init__(self,length):\n",
    "        self.lenth=length\n",
    "    @abstractmethod\n",
    "    def area(self):\n",
    "        pass\n",
    "class Circle(shape):\n",
    "    def __init__(self,length):\n",
    "        self.length=length\n",
    "    def area(self):\n",
    "        return 3.14*self.length*self.length\n",
    "class Squre(shape):\n",
    "    def __init__(self,length):\n",
    "        self.length=length\n",
    "    def area(self):\n",
    "        return self.length*self.length\n",
    "circle=Circle(10)\n",
    "print(circle.area())\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe612459",
   "metadata": {},
   "source": [
    "7、通过键盘输入方程式 y=ax^2+bx+c 中的系数 a,b,c后先解方程，如果有实数根x1和x2，则绘制 x 在 [1.1*x1,1.1*x2 ，(x1<=x2)] 范围内的函数波形图。图表需包含标题，说明当前函数表达式，中文显示正常，x,y轴有刻度，函数波形和x,y轴颜色有区别。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "41d6d79b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "两个根x1=-4.561552812808831,x2=-0.4384471871911697\n"
     ]
    }
   ],
   "source": [
    "a=float(input(\"请输入a的值\"))\n",
    "b=float(input(\"请输入b的值\"))\n",
    "c=float(input(\"请输入c的值\"))\n",
    "\n",
    "def func(a,b,c):\n",
    "    delta=b*b-4*a*c\n",
    "    if delta<0:\n",
    "        print(\"该函数无实根\")\n",
    "        return None,None\n",
    "    elif delta==0:\n",
    "        x1=(-b)/(2*a)\n",
    "        print(f\"该函数一个实数根x1=x2={x1:.2f}\")\n",
    "        return x1,x1\n",
    "    else:\n",
    "        # x1=(-b)-delta**0.5]/(2*a)\n",
    "        # x2=[(-b)+delta**0.5]/(2*a)\n",
    "        x1=((-b)-delta**0.5)/(2*a)\n",
    "        x2=((-b)+delta**0.5)/(2*a)\n",
    "        print(f\"两个根x1={x1:.2f},x2={x2:.2f}\")\n",
    "        return x1,x2\n",
    "x1,x2=func(a,b,c)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "5333d19b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 500x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "plt.rcParams[\"font.sans-serif\"]=\"SimHei\"\n",
    "plt.rcParams[\"axes.unicode_minus\"]=False\n",
    "\n",
    "if x1 is not None and x2 is not None:\n",
    "    x=np.linspace(1.1*x1,1.1*x2,400)\n",
    "    y=a*x**2+b*x+c\n",
    "    plt.figure(figsize=(5,3))\n",
    "    plt.plot(x3,y)\n",
    "    plt.title(\"y=a*x**2+b*x+c\")\n",
    "    plt.xlabel(\"x\")\n",
    "    plt.ylabel(\"y\")\n",
    "    #plt.savefig(\"二元函数曲线.png\")\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7d6191c9",
   "metadata": {},
   "source": [
    "8、用随机生成半年（6个月）的销售数据，然后绘制曲线图。（日期和销售额，使用pandas）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "465f0564",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '2025上半年销售数据')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "dates=pd.date_range(\"2025-1-1\",\"2025-6-30\",freq=\"ME\")\n",
    "sales=np.random.randint(1000,5000,len(dates))\n",
    "df=pd.DataFrame({\"日期\":dates, \"销售额\":sales})\n",
    "plt.figure()\n",
    "plt.plot(dates,sales,c=\"g\")\n",
    "plt.xlabel(\"月份\")\n",
    "plt.ylabel(\"销售额\")\n",
    "plt.title(\"2025上半年销售数据\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f3393565",
   "metadata": {},
   "source": [
    "9、实现一个基于 JSON 格式的信息管理程序。该程序需支持以下菜单功能：\n",
    "1)添加记录：2)删除记录；3)查找记录;  4)退出 \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "10c970f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import os \n",
    "\n",
    "data=(\"data.json\")\n",
    "def init_data():\n",
    "    if not os.path.exists(data):\n",
    "        with open(\"data.json\",\"w\") as f:\n",
    "            json.dump([],f)\n",
    "\n",
    "def load_data():\n",
    "    with open('data.json',\"r\") as f:\n",
    "        data=json.load(f)\n",
    "        return data\n",
    "def save_data(data):\n",
    "    with open(\"data.json\",\"w\") as f:\n",
    "        json.dump(data,f)\n",
    "def add_data():\n",
    "    data=load_data()\n",
    "    record={\n",
    "        \"name\":input(\"name\"),\n",
    "        \"age\":input(\"age\")\n",
    "    }\n",
    "    data.append(record)\n",
    "    save_data(data)\n",
    "def find_data():\n",
    "    name=input(\"name\")\n",
    "    data=load_data()\n",
    "    target=[r for r in data if r[\"name\"]==name]\n",
    "    print(*target)\n",
    "\n",
    "def del_data():\n",
    "    name=input(\"name\")\n",
    "    data=load_data()\n",
    "    data1=[r for r in data if r[\"name\"]!=name]\n",
    "    save_data(data1)\n",
    "\n",
    "\n",
    "if __name__==\"__main__\":\n",
    "    #add_data()\n",
    "    #find_data()\n",
    "    del_data()\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "61b68db0",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "67dbdc51",
   "metadata": {},
   "source": [
    "10、实现一个基于 SQLite 数据库的信息管理程序,操作数据表tab1，并支持以下菜单功能：\n",
    "1)添加记录：2)删除记录；3)查找;4)导出到 CSV "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c92ebce8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sqlite3\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "def init_db():\n",
    "    conn=sqlite3.connect(\"information.db\")\n",
    "    cursor=conn.cursor()\n",
    "    cursor.execute(\"\"\"create table if not exists tab1(\n",
    "    id integer primary key autoincrement,\n",
    "    name text not null,\n",
    "    age integer,\n",
    "    phone text\n",
    "    )\"\"\")\n",
    "    conn.commit()\n",
    "    conn.close()\n",
    "def add_record():\n",
    "    name=input(\"姓名\")\n",
    "    age=int(input(\"年龄\"))\n",
    "    phone=input(\"电话\")\n",
    "\n",
    "    conn=sqlite3.connect(\"information.db\")\n",
    "    cursor=conn.cursor()\n",
    "    cursor.execute(\"\"\"insert into tab1 (name,age,phone) values (?,?,?)\"\"\",\n",
    "    (name,age,phone))\n",
    "    conn.commit()\n",
    "    conn.close()\n",
    "def delete_record():\n",
    "    name=input(\"请输入要删除的姓名\")\n",
    "    conn=sqlite3.connect(\"information.db\")\n",
    "    cursor=conn.cursor()\n",
    "    cursor.execute(\"\"\"delete from tab1 where name = ?\"\"\",(name,))\n",
    "    conn.commit()\n",
    "    conn.close()\n",
    "def find_record():\n",
    "    name=input(\"请输入要查询的姓名\")\n",
    "    conn=sqlite3.connect(\"information.db\")\n",
    "    cursor=conn.cursor()\n",
    "    result=cursor.execute(\"\"\"select * from tab1 where name = ?\"\"\",(name,))\n",
    "    print(*result)\n",
    "    conn.commit()\n",
    "    conn.close()\n",
    "def to_csv():\n",
    "    conn=sqlite3.connect(\"information.db\")\n",
    "    #cursor=conn.cursor()\n",
    "    df=pd.read_sql(\"select * from tab1\",conn)\n",
    "    df.to_csv(\"infor.csv\")\n",
    "    conn.commit()\n",
    "    conn.close()\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "if __name__==\"__main__\":\n",
    "    init_db()\n",
    "    #add_record()\n",
    "    #find_record()\n",
    "    to_csv()\n",
    "\n",
    "    \n",
    "\n",
    "\n"
   ]
  }
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